Search engines as they currently exist on the Internet are used by people all over the world to find and download data objects of interest that reside on servers. Typically, these search engines periodically examine many servers on the Internet to see what data objects each server contains. Thereafter, the search engine constructs an index of each server's contents, and links the contents to that server's location.
The construction of the index is a time consuming task, and because of the relative cost involved to the servers and the search engine, it cannot be done very often. The timeliness of the information created by the search engine is sacrificed in order to reduce the burden on the index builder of the search engines and the servers that contain the data being searched.
This means that the search engine index is quickly out of date. For some types of data objects, this matters very little, since the data objects are created and modified relatively slowly. However, for data objects that are created and removed relatively often, the search engine indices are impractical, and for data objects that are added and removed daily, the standard search engines are practically useless. In addition, the current paradigm assumes a relatively static server environment, but in an environment where servers come up and go down relatively frequently and data objects are added and deleted hourly or more frequently, the standard search engine methodology is not useful at all.
Thus, it can be seen that there is a need for an Internet search engine that maintains an up-to-date index of data content residing on servers that are currently connected to the Internet.
There is a further need for a real-time search engine that significantly reduces the cost of constructing a search engine index using methods employed by the prior art.